Estimation of optimal cutting parameters of plane turning using quantum inspired evolutionary algorithm
نویسندگان
چکیده
Turning is a versatile machining process that involves different cutting parameters and conditions. The surface finish is the vital design requirement as it is a key indicator of quality of the work piece. This work, presents the application of Quantum Inspired Evolutionary Algorithm (QIEA), that essentially exploits some principles of quantum mechanics such as Q-bits, superposition, quantum gate and quantum measurement, for the process optimization of plane turning. The QIEA estimated optimal cutting parameters i.e., cutting speed, feed rate, tool nose radius and depth of cut of plane turning for improved surface finish within the operating conditions. The results are compared with real coded genetic algorithm (RCGA) and differential evolution algorithm (DEA). The results obtained by Quantum Inspired Evolutionary Algorithm are better than those reported with RCGA and are comparable to those of DEA.
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